In the field of image processing, there is an ongoing effort to provide an efficient and reliable way to detect an object of interest within a field of view (e.g., a scene) of an imaging device. However, such techniques rely on cumbersome processing intensive routines to detect the presence of an object of interest in a scene.
For example, general subtraction methods may be used to obtain a foreground of a scene that can be analyzed to determine if an object is present and, if so, further analyzed to determine an identification of the object detected. Several issues arising from conventional techniques such as image occlusion and defragmentation may make object detection unreliable. Moreover, these techniques may not be suited for real time processing applications due to the excessive amount of image data available to process. Thus, there is a need for object detection solutions that may provide performance or other advantages over conventional object detection systems.